Physics-Based Cell Layout Redesign for Dynamic Grid Spacing
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Solution Overview
Problem
Manipulating grid-based layouts in computing applications, such as resizing or repositioning cells, often results in unintended overlaps or uniform changes to entire rows or columns, leading to a poor user experience due to the lack of maintenance of grid spacing and dynamic adjustment of adjacent cells.
Innovation Solution
Implementing a physics-based algorithm that reconfigures proximate cells in a cell grid based on edge relations and opposing forces applied during user input, allowing for dynamic resizing and repositioning while maintaining grid layout spacing by adding or deleting cells as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a user resizes or repositions one cell in a cell grid, then the user can modify the cell layout, but the grid spacing is not maintained and overlaps or unintended results occur
Solution Approach 1:
The system dynamically adjusts the positions and sizes of multiple cells in response to user manipulation of a single cell. Instead of static grid positions, the cells respond dynamically to maintain grid spacing, automatically repositioning themselves to fill gaps and prevent overlaps while preserving the overall grid structure.
Solution Approach 2:
The system provides immediate feedback when a user manipulates a cell by automatically adjusting other cells in the grid. The grid spacing constraint acts as a feedback mechanism that continuously monitors and corrects cell positions to maintain proper spacing, preventing overlaps and unintended results.
2Adaptability or versatility
If a user selects one cell and changes its width or height, then the cell size is modified, but the entire row or column is repositioned uniformly
Solution Approach 1:
The system applies local quality by allowing individual cells to have different sizes and positions while maintaining grid spacing only where necessary. When a user resizes a cell, only the affected local area of the grid is adjusted, not the entire row or column uniformly. This enables precise control over specific cells without forcing uniform changes across related cells.
3Area of moving object
If a user increases the size of one cell, then the cell area is expanded, but the entire cell grid or cell table increases in size
Solution Approach 1:
The system uses dynamic adjustment where other cells in the grid automatically respond to the size change of one cell. When a cell is expanded, neighboring cells dynamically shift position and adjust their boundaries to accommodate the change, allowing individual cell area to increase without forcing the entire grid to expand.
Solution Approach 2:
The system merges the behavior of multiple cells into a coordinated response. When one cell is resized, the adjustment is distributed across multiple cells in the grid through automatic repositioning and resizing operations, combining their movements to maintain overall grid integrity while allowing individual cell area changes.
4Adaptability or versatility
If a user manipulates cells in a cell grid, then the cell layout can be customized, but a series of adjustments to other cells is required to achieve the desired result
Solution Approach 1:
The system performs self-service by automatically adjusting other cells in the grid when a user manipulates one cell. The grid spacing constraints and physics-based algorithms enable the system to self-correct cell positions and sizes without requiring manual intervention, eliminating the need for users to make multiple sequential adjustments to achieve proper grid layout.
Data Source
AI summary
In embodiments of physics-based cell layout redesign, a computing device displays a cell layout interface that includes cells in a cell grid, and the computing device implements a physics-based algorithm as a computer application that can receive a redesign input to manipulate a cell in the cell layout interface. The physics-based algorithm is implemented to then determine one or more of the cells that are proximate the manipulated cell based on edge relations between an edge of the manipulated cell and respective edges of the one or more cells. The physics-based algorithm can then reconfigure the one or more proximate cells based on the redesign input to the manipulated cell and the edge relations between the edges of the cells.